Class implementing the LSC (Linear Spectral Clustering) superpixels algorithm described in [LiCVPR2015LSC].
More...
|
virtual void | enforceLabelConnectivity (int min_element_size=25)=0 |
| Enforce label connectivity.
|
|
virtual void | getLabelContourMask (OutputArray image, bool thick_line=true) const =0 |
| Returns the mask of the superpixel segmentation stored in SuperpixelLSC object.
|
|
virtual void | getLabels (OutputArray labels_out) const =0 |
| Returns the segmentation labeling of the image.
|
|
virtual int | getNumberOfSuperpixels () const =0 |
| Calculates the actual amount of superpixels on a given segmentation computed and stored in SuperpixelLSC object.
|
|
virtual void | iterate (int num_iterations=10)=0 |
| Calculates the superpixel segmentation on a given image with the initialized parameters in the SuperpixelLSC object.
|
|
| Algorithm () |
|
virtual | ~Algorithm () |
|
virtual void | clear () |
| Clears the algorithm state.
|
|
virtual bool | empty () const |
| Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read.
|
|
virtual String | getDefaultName () const |
|
virtual void | read (const FileNode &fn) |
| Reads algorithm parameters from a file storage.
|
|
virtual void | save (const String &filename) const |
|
void | write (const Ptr< FileStorage > &fs, const String &name=String()) const |
| simplified API for language bindings This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.
|
|
virtual void | write (FileStorage &fs) const |
| Stores algorithm parameters in a file storage.
|
|
Class implementing the LSC (Linear Spectral Clustering) superpixels algorithm described in [LiCVPR2015LSC].
LSC (Linear Spectral Clustering) produces compact and uniform superpixels with low computational costs. Basically, a normalized cuts formulation of the superpixel segmentation is adopted based on a similarity metric that measures the color similarity and space proximity between image pixels. LSC is of linear computational complexity and high memory efficiency and is able to preserve global properties of images
virtual void cv::ximgproc::SuperpixelLSC::iterate |
( |
int |
num_iterations = 10 | ) |
|
|
pure virtual |
Python: |
---|
| cv.ximgproc.SuperpixelLSC.iterate( | [, num_iterations] | ) -> | None |
Calculates the superpixel segmentation on a given image with the initialized parameters in the SuperpixelLSC object.
This function can be called again without the need of initializing the algorithm with createSuperpixelLSC(). This save the computational cost of allocating memory for all the structures of the algorithm.
- Parameters
-
num_iterations | Number of iterations. Higher number improves the result. |
The function computes the superpixels segmentation of an image with the parameters initialized with the function createSuperpixelLSC(). The algorithms starts from a grid of superpixels and then refines the boundaries by proposing updates of edges boundaries.